Bootstrap Hypothesis Test - University of California, Los ...
> t.test(betterspeed,alternative="two.sided",mu=33.02) One Sample t-test data: betterspeed t = -4.6078, df = 17, p-value = 0.0002508 alternative hypothesis: true mean is not equal to 33.02 95 percent confidence interval: 23.83863 29.60582 sample estimates: mean of x 26.72222 As you can see, the p-value is not exactly 0, but is quite small.
Tags:
Tests, Alternatives, Hypothesis, Bootstrap, Alternative hypothesis, Bootstrap hypothesis test
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
Documents from same domain
Estimation of Space–Time Branching Process Models in ...
www.stat.ucla.eduEstimation of Space–Time Branching Process Models in Seismology Using an EM–Type Algorithm Alejandro VEEN and Frederic P. SCHOENBERG Maximum likelihood estimation of branching point process models via numerical optimization procedures can be unstable and computa-tionally intensive. We explore an alternative estimation method based on the ...
Using, Model, Process, Branching, Frederic, Seismology, Branching process models in seismology using
Midterm Exam 1 Review — Chapters 1, 2, 4 and 5
www.stat.ucla.eduStats 11 (Fall 2004) Lecture Note Instructor: Hongquan Xu Introduction to Statistical Methods for Business and Economics Midterm Exam 1 Review — Chapters 1, 2, 4 …
Business, Exams, Review, Chapter, Midterm, Midterm exam 1 review chapters
Distributions related to the normal distribution - Website
www.stat.ucla.eduDistributions related to the normal distribution Three important distributions: Chi-square (˜2) distribution. tdistribution. Fdistribution. Before we discuss the ˜2;t, and F distributions here are few important things about the gamma distribution.
Distribution, Related, Normal, Distributions related to the normal distribution
The Central Limit Theorem - Main Concepts
www.stat.ucla.eduCentral limit theorem - proof For the proof below we will use the following theorem. Theorem: Let X nbe a random variable with moment generating function M Xn (t) and Xbe a random variable with moment generating function M X(t). If lim n!1 M Xn (t) = M X(t) then the distribution function (cdf) of X nconverges to the distribution function of Xas ...
Central, Limits, Theorem, Central limit theorem, The central limit theorem
Describing Relationships between Two Variables
www.stat.ucla.eduIs the relationship strong (clear patterns) or weak (fuzzy patterns)? Here are some examples: This data comes from class. The picture comes from plotting each person’s height and weight. For example ( 74, 180), (69, 175), (76, 170), etc. This is a positive relation, fairly …
Covariance and correlation - Main Concepts
www.stat.ucla.eduCorrelation: However, the covariance depends on the scale of measurement and so it is not easy to say whether a particular covariance is small or large. The problem is solved by standardize the value of covariance (divide it by ˙ X˙ Y), to get the so called coe cient of correlation ˆ XY. ˆ= cov(X;Y) ˙ X˙ Y; Always, 1 ˆ 1 cov(X;Y) = ˆ ...
Stochastic Difierential Equations
www.stat.ucla.eduthe stochastic calculus. Problem 4 is the Dirichlet problem. Although this is purely deterministic we outline in Chapters VII and VIII how the introduc-tion of an associated Ito difiusion (i.e. solution of a stochastic difierential equation) leads to a simple, intuitive and useful stochastic solution, which is
Equations, Difierential, Stochastic, Stochastic difierential equations
Normal distribution - University of California, Los Angeles
www.stat.ucla.eduWe say that a random variable X follows the normal distribution if the probability density function of Xis given by f(x) = 1 ˙ p 2ˇ e 1 2 (x ˙)2; 1 <x<1 This is a bell-shaped curve. We write X˘N( ;˙). We read: Xfollows the normal distribution (or Xis normally distributed) with mean , and standard deviation ˙.
Z f x dx = 1 be a continuous r.v. f x
www.stat.ucla.eduSuppose Xfollows the exponential distribution with = 1. If Y = p X nd the pdf of Y. Example 2 Let X ˘N(0;1). If Y = eX nd the pdf of Y. Note: Y it is said to have a log-normal distribution. Example 3 Let Xbe a continuous random variable with pdf f(x) = 2(1 x);0 x 1. If Y = 2X 1 nd the pdf of Y. Example 4 Let Xbe a continuous random variable ...
Related documents
Introduction to Hypothesis Testing - SAGE Publications Inc
www.sagepub.comAn alternative hypothesis (H 1) is a statement that directly contradicts a null hypothesis by stating that that the actual value of a population parameter is less than, greater than, or not equal to the value stated in the null hypothesis. The alternative hypothesis states what we think is wrong about the null hypothesis, which is needed for ...
Sage, Publication, Alternatives, Hypothesis, Sage publications inc, Alternative hypothesis
Null hypothesis vs. alternative hypothesis
courses.cit.cornell.eduEcon 620 Null hypothesis vs. alternative hypothesis Suppose that we have data y =(y1,···,yn) and the data is generated by the true probability distribution Pθ0, from a family of probability distribution Pθ indexed by θ ∈ Θ. We can partition the parameter space Θ into two subsets, Θ0 and ΘA. Now, consider the following two hypothesis;
DEVELOPING HYPOTHESIS AND RESEARCH QUESTIONS
www.public.asu.eduThe null hypothesis represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved. Has serious outcome if incorrect decision is made! The alternative hypothesisis a statement of what a hypothesis test is set up to establish.
Statistical Hypothesis Testing
www.afit.eduThe alternative hypothesis is the claim to be tested; it reflects what the tester is trying to show. To illustrate the concept of null and alternative hypotheses, consider a criminal trial. In the criminal justice system, the defendant is presumed innocent until …
Hypothesis Testing for Proportions
gchang.people.ysu.eduHypothesis Testing for Proportions 2 HT - 7 Statistical Hypothesis Alternative hypothesis (H 1 or Ha) Usually corresponds to research hypothesis and opposite to null hypothesis, often has >, < or ≠notation in testing mean. Example: Ha: p ≠30% or Ha: Percentage of votes for A is not 30%. HT - 8 Hypotheses Statements Example
Hypothesis Testing - Duke University
www2.stat.duke.edu23.1 How Hypothesis Tests Are Reported in the News 1. Determine the null hypothesis and the alternative hypothesis. 2. Collect and summarize the data into a test statistic. 3. Use the test statistic to determine the p-value. 4. The result is statistically significant if the p-value is less than or equal to the level of significance.
Chapter 6 Hypothesis Testing - University of Pittsburgh
sites.pitt.eduAn Alternative Decision Rule using the p - value Definition The p-value is defined as the smallest value of α for which the null hypothesis can be rejected. If the p-value is less than or equal to α ,we reject the null hypothesis (p ≤ α) If the p-value is greater than α ,we do not reject the null hypothesis (p > α)